The Vehicle Analogy
Imagine you run a business and you need different tools for different tasks. For example, you wouldn't use a heavy-duty truck for a quick trip to the grocery store or a sports car to haul construction materials. Similarly, when companies move their data to the cloud, they often choose one main tool to store and process all their data, like putting everything in one big warehouse or lake. However, this warehouse or lake is very expensive to use for all kinds of tasks, especially for small or less important ones. Gartner (2023) notes that most organisations overspend in the cloud because they default to a single, high-cost compute layer for all workloads, even though most tasks do not require it.
Not all tasks need such a powerful and costly warehouse
The problem is that not all tasks need such a powerful and costly warehouse. In fact, most of these tasks are small and don't need that much power, making this approach very costly and inefficient. McKinsey’s analysis of cloud waste (2023) highlights that up to 70% of cloud spend can be eliminated simply by aligning workload types to appropriate compute resources.
Price Performant Compute (PPC)
I call this price performant compute (PPC). Thinking back to the vehicle analogy, PPC is like making sure you're using the right vehicle for the right job to get the best value for your money.
In the context of managing data for an organisation, "price performant compute" means using the most cost-effective and efficient computing resources for each specific task. Instead of running every data task on a super expensive and powerful system, which can be very costly, we use the appropriate system that fits the need of the task. For example, simple tasks run on cheaper systems, while more complex tasks that need more power use the more expensive systems.
This approach ensures that the company is spending its money wisely and getting the best performance possible for each task, without overspending on computing power that isn't needed. It's all about matching the task to the right resource to optimize costs and performance.
The Challenge of Managing Multiple Repositories
Imagine you own a business with several storage locations for different types of items. You have a warehouse for large equipment, a storage unit for office supplies, and a refrigerated unit for perishable goods. While each location is ideal for its specific items, managing all these different storage spots can become complicated. You need to keep track of where everything is, ensure each location is maintained properly, and move items between locations as needed. This can be time-consuming and requires a lot of coordination.
Similarly, in a company, storing different types of data in different repositories that are best suited for each type makes sense. However, managing all these separate repositories can be challenging. You need to know where all your data is stored, ensure each repository is functioning correctly, and manage the movement and processing of data across these repositories. This can be complex and require significant effort and resources. IDC (2024) highlights that multi-repository ecosystems often introduce silos and operational overhead unless unified by a governance or control plane.
Meet Latttice!
Imagine you have a smart assistant for your business that can manage all your different storage locations, warehouses, storage units, refrigerated units, and more. This assistant knows exactly where everything is and can automatically move items to the right place and fetch them when needed. This is what Latttice does for your data.
What Latttice provides:
Unified Access Point
A single, easy-to-use entry point to access all your data, no matter where it is stored. Just like having one app to manage all your different storage locations, Latttice gives you one platform to access and control all your data repositories.
Smart Task Routing
Easy development of data products across multiple repositories, with AI powered, zero code, functionality. This rapidly enables you to perform tasks with your data, against the most suitable repository. For instance, if you need to run an AI task, it executes against a repository designed for AI workloads. If you need to generate a business report, it executes tasks against a repository best suited for that purpose. This ensures that each task is handled efficiently and cost-effectively. Forrester's 2024 State of Data Strategy report specifically highlights the importance of zero-code and AI-enabled data access for business teams.
Simplified Management
Latttice takes care of the complex coordination between different data repositories. You don't have to worry about manually managing each one or moving data around. Latttice ensures everything works together smoothly, reducing the hassle and effort on your part.
Conclusion
The concept of price performant compute (PPC) addresses the inefficiency and high costs associated with running all data tasks on expensive computing resources. By storing different types of data in repositories tailored to specific workloads, such as AI or business intelligence, companies can optimize their computing expenses. Latttice simplifies this process by providing a centralized control plane that unifies access to all data repositories, smartly executing tasks against the appropriate systems. This approach ensures efficient use of resources, reduces costs, and streamlines data management, allowing companies to focus on leveraging their data for better decision-making without the burden of managing complex and capital-intensive infrastructures.
